Strengthening Democracy Through Participation and Critical Adult Education
Bibliographic record
Abstract
Reducing education to pure technique is to anesthetize curiosity (Freire, 1997). Neoliberal policies privilege private interests and promote a model of education based on competition and consumerism (Harvey, 2005). This model of education perpetuates and increases inequalities. It also affects education whose priority is not to deliver learners with an immediate financial return. I claim that critical citizenship education and adult education principles have the potential to oppose the neoliberal forces in education. Additionally, promoting a “thick” vision of democracy (Carr, 2008) underpinned in citizens’ participation is a strong tool to counter neoliberal policies. In this study, I will look into the Brazilian participatory budget initiative as a tool to promote democracy and citizenship. Finally, I will propose a theoretical framework that incorporates strong adult education principles to strengthen democracy in times of neoliberalism.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".